This section will discuss the SFQM features that enable Measuring Telco Traffic
and Performance KPIs.

Fig. 5.1 Measuring Telco Traffic and Performance KPIs

The very first thing SFQM enabled was a call-back API in DPDK and an
associated application that used the API to demonstrate how to timestamp
packets and measure packet latency in DPDK (the sample app is called
rxtx_callbacks). This was upstreamed to DPDK 2.0 and is represented by
the interfaces 1 and 2 in Figure 1.2.

The second thing SFQM implemented in DPDK is the extended NIC statistics API,
which exposes NIC stats including error stats to the DPDK user by reading the
registers on the NIC. This is represented by interface 3 in Figure 1.2.

For DPDK 2.1 this API was only implemented for the ixgbe (10Gb) NIC driver,
in association with a sample application that runs as a DPDK secondary
process and retrieves the extended NIC stats.

For DPDK 2.2 the API was implemented for igb, i40e and all the Virtual
Functions (VFs) for all drivers.

For DPDK 16.07 the API migrated from using string value pairs to using id
value pairs, improving the overall performance of the API.

With the features SFQM enabled in DPDK to enable measuring Telco traffic and
performance KPIs, we can now retrieve NIC statistics including error stats and
relay them to a DPDK user. The next step is to enable monitoring of the DPDK
interfaces based on the stats that we are retrieving from the NICs, by relaying
the information to a higher level Fault Management entity. To enable this SFQM
has been enabling a number of plugins for collectd.

collectd is a daemon which collects system performance statistics periodically
and provides a variety of mechanisms to publish the collected metrics. It
supports more than 90 different input and output plugins. Input plugins retrieve
metrics and publish them to the collectd deamon, while output plugins publish
the data they receive to an end point. collectd also has infrastructure to
support thresholding and notification.

Within collectd notifications and performance data are dispatched in the same
way. There are producer plugins (plugins that create notifications/metrics),
and consumer plugins (plugins that receive notifications/metrics and do
something with them).

Statistics in collectd consist of a value list. A value list includes:

Values, can be one of:

Derive: used for values where a change in the value since it’s last been
read is of interest. Can be used to calculate and store a rate.

Counter: similar to derive values, but take the possibility of a counter
wrap around into consideration.

Gauge: used for values that are stored as is.

Absolute: used for counters that are reset after reading.

Value length: the number of values in the data set.

Time: timestamp at which the value was collected.

Interval: interval at which to expect a new value.

Host: used to identify the host.

Plugin: used to identify the plugin.

Plugin instance (optional): used to group a set of values together. For e.g.
values belonging to a DPDK interface.

Type: unit used to measure a value. In other words used to refer to a data
set.

Type instance (optional): used to distinguish between values that have an
identical type.

meta data: an opaque data structure that enables the passing of additional
information about a value list. “Meta data in the global cache can be used to
store arbitrary information about an identifier” [7].

The figure above shows the DPDK L2 forwarding application running on a compute
node, sending and receiving traffic. collectd is also running on this compute
node retrieving the stats periodically from DPDK through the dpdkstat plugin
and publishing the retrieved stats to Ceilometer through the ceilometer plugin.